Download pdf guide - VSN International

15 Examples 293The data are taken from a large genetic study on Coopworth lambs. A total of 5traits, namely weaning weight (wwt), yearling weight (ywt), greasy fleece weight(gfw), fibre diameter (fdm) and ultrasound fat depth at the C site (fat) weremeasured on 7043 lambs. The lambs were the progeny of 92 sires and 3561 dams,produced from 4871 litters over 49 flock-year combinations. Not all traits weremeasured on each group. No pedigree data was available for either sires or dams.The aim of the analysis is to estimate heritability (h 2 ) of each trait and to estimatethe genetic correlations between the five traits. We will present two approaches,a half-sib analysis and an analysis based on the use of an animal model, whichdirectly defines the genetic covariance between the progeny and sires and dams.The data fields included factors defining sire, dam and lamb (tag), covariates suchas age, the age of the lamb at a set time, brr the birth rearing rank (1 = bornsingle raised single, 2 = born twin raised single, 3 = born twin raised twin and 4= other), sex (M, F) and grp a factor indicating the flock-year combination.Half-sib analysisIn the half-sib analysis we include terms for the random effects of sires, dams andlitters. In univariate analyses the variance component for sires is denoted byσs 2 = 1 4 σ2 A where σ2 A is the additive genetic variance, the variance component fordams is denoted by σd 2 = 1 4 σ2 A +σ2 m where σm 2 is the maternal variance componentand the variance component for litters is denoted by σl 2 and represents variationattributable to the particular mating.For a multivariate analysis these variance components for sires, dams andlitters are, in theory replaced by unstructured matrices, one for each term.Additionally we assume the residuals for each trait may be correlated. Thus forthis example we would like to fit a total of 4 unstructured variance models. Forsuch a situation, it is sensible to commence the modelling process with a series ofunivariate analyses. These give starting values for the diagonals of the variancematrices, but also indicate what variance components are estimable. The ASRemljob for the univariate analyses isMultivariate Sire & Dam modeltagsire 92 !Idam 3561 !Igrp 49sexbrr 4litter 4871